Lecture Notes on Quantum Annealing by Berta Trules Clava

Introduction

• Speaker: Berta Trules Clava, Senior Superconductor IC Designer at D-Wave
• Background: Master in Electrical Engineering from the University of Twente
• Focus: Basics and hardware of quantum annealers

Overview of D-Wave

• History: 25 years in the business, 5 generations of quantum computers
• Access: Cloud service called Leap
• Tools: Developer tools and Professional Services
• Focus of Talk: Hardware aspects of quantum annealing
• Upcoming Session: Software bootcamp by a colleague named Sarah

Quantum Annealing (QA)

• Definition: Uses quantum mechanical effects to find the global minimum of a function in optimization problems
• Applications: Logistics, manufacturing, machine learning (e.g., scheduling food deliveries for Save On Foods)

Key Concepts

System Hamiltonian

• Definition: A function that maps states of a system to its energies
• Example: Ball on a hill
• Ground State: Lowest energy state of the system

Adiabatic Theorem

• Principle: Start in the lowest energy state and evolve the Hamiltonian slowly to remain in the lowest energy state

Quantum Annealing Process

1. Initial Hamiltonian: System in ground state
2. Evolution: Sweep Hamiltonian to include problem constraints
3. Tunneling: Wave function delocalizes, enabling tunneling through barriers
4. Final Hamiltonian: System in lowest energy state reflects the optimal solution

Hardware Implementation

Components

• Qubits and Couplers: Made using semiconductor fabrication processes
• Superconducting Qubits: Require cooling below the critical temperature
• Control Circuitry: Used for programming H and J values

System Architecture

• Processor Box: Contains electronics, noise shield, and cooling system
• Microchip: Inside the box, houses the qubits
• Qubit Design: Multi-layer metal and dielectric layers

Superconductivity

• Properties: Zero DC resistance, flux expulsion
• Josephson Junctions: Critical for qubit function
  • Made from superconductor materials separated by an insulating material
  • Important Equations: Involves critical current (IC) and phase difference

Qubit and Coupler Design

• Quantum Flux Parametron (QFP): Basic qubit design
• DC Squid: Allows tuning of Josephson Junctions
• Compound Josephson Junctions: Enhance tunability and control
• Couplers: Used to establish relationships between qubits
  • Enable both positive and negative couplings

Processor Layout

• Unit Cells: Basic building blocks containing multiple qubits
• Qubit Coupling: Each qubit coupled to others through several couplers
• Calibration Techniques: Manage crosstalk and process variations

Advanced Architectures

• Chimera and Pegasus: Different architectures for qubit and coupler arrangements
• Upcoming Topologies: Example of an advanced topology (Advantage with 5000+ qubits)

Applications and Real-World Use Cases

• Optimization Problems: Examples include scheduling, portfolio optimization, manufacturing processes
• Future Work: Hybrid models combining quantum annealing with other methodologies

Q&A Highlights

• Differences between Gate-Based and Annealing: Optimization vs. broader applications
• Machine Learning: Experimental applications in classification, feature selection
• Evolution Timing for QA: Between hundreds of nanoseconds to microseconds
• Hardware Design Tools: Cadence for layout, open-source tools for simulation (e.g., WSpice)

Additional Resources

• Books and Texts: For deeper understanding of superconductivity and device physics
• Leap Account: Sign-up for access to cloud services and training sessions

Sarah's Upcoming Session Preview: Practical applications and hands-on demo on the Leap platform.